SUMMARY/ABSTRACT Alzheimer?s disease (AD) prevalence is projected to triple by 2050. There is increasing emphasis on the need for preventive interventions targeting cognitive decline and onset of mild cognitive impairment (MCI) or AD given the lack of treatments available. Sleep disturbances are common among older individuals and a growing body of evidence suggests that disrupted sleep may be a precursor of cognitive decline and MCI. By partnering with the ongoing, well-established Einstein Aging Study Program Project (EAS; NIA- AG03949), we will add ambulatory measures of sleep health to the EAS intensive ?burst? cognitive assessments in which smartphone technology is applied to assess cognitive performance multiple times per day, over 14-days, in naturalistic settings. The project will measure the major dimensions of sleep health by adding daily measures of sleep health (wrist actigraphy and daily ecological momentary assessment of self- reported sleep quality and daytime alertness), as well as an ambulatory measure of overnight oxygen desaturation to the EAS burst protocol which is following 500 community based older adults over four annual evaluations. Using this approach, we will assess both short-term (over days) and long term (over years) effects of indices of sleep health on cognitive performance, cognitive decline and MCI risk. we will be the first study to concurrently assess ecologically valid measures both of sleep health and cognitive performance using an intensive measurement design in a cohort of older adults. By minimizing the effects of naturally occurring variability in both indices of sleep health and cognitive performance, the intensive measurement improves the reliability of estimates and improves sensitivity for detecting change over time. This will thus clarify how changes in sleep health are associated with cognitive decline. Additionally, this design will also allow for novel explorations of intra-individual variability including: characterizing the proximal effects of sleep health on cognition (day-to-day effects); determining whether variability in sleep health predicts cognitive decline over the long term; and determining whether individuals vulnerable to the short-term effects of poor sleep on cognition are at increased risk for long term cognitive decline. Longitudinal assessments over annual follow-ups will allow us to advance understanding of the relation between sleep and cognitive decline by defining associations between longitudinal changes in sleep with changes in cognition. The proposed new sleep measures combined with the EAS burst and core assessments will allow us to do so over multiple dimensions of sleep health and multiple domains of cognitive function. By addressing gaps in the literature, the proposed study will inform ways to target early interventions for prevention or delay of cognitive decline by better understanding the proximal effects of sleep and by identifying the particular dimensions of sleep and domains of cognitive performance that are most closely related.